【摘要】 针对MIMO雷达稀疏阵列优化问题，提出一种改进哈里斯鹰算法的MIMO雷达阵列图优化策略。首先通过融合重心邻域搜索与状态转移算子提高哈里斯鹰算法的局部搜索能力，并在迭代过程中加入天牛须搜索策略，使得算法在迭代过程中始终保持较高种群多样性，提高算法的收敛精度和收敛速度。其次以等效虚拟收发波束的旁瓣峰值最小为目标函数，将改进后的鹰群算法进行优化求解。最后将所得实验结果与其他优化策略所得实验结果进行对比分析，所提算法所得旁瓣峰值更小，提高了MIMO雷达的识别能力和工作性能。更多还原

【Abstract】 To address the sparse array optimization problem of MIMO radar, an improved Harris Eagle algorithm for MIMO radar array graph optimization strategy is proposed. Firstly, the local search ability of Harris Eagle algorithm is improved by integrating the barycentric neighborhood search and state transition operator, and the horntail search strategy is added in the iteration process, so that the algorithm always maintains a high population diversity in the iteration process, and improves the convergence accuracy and convergence speed of the algorithm. Secondly, taking the minimum sidelobe peak value of equivalent virtual transmitting and receiving beam as the objective function, the improved eagle swarm algorithm can be optimized. Finally, the experimental results are compared with those of other optimization strategies. The proposed algorithm has a smaller sidelobe peak value, which improves the recognition ability and performance of MIMO radar.更多还原